Create README.md

README.md

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+---
+language: en
+license: apache-2.0
+tags:
+- quantum-computing
+- signal-processing
+- error-correction
+- transformer
+---
+
+# quantum_noise_denoiser_v1
+
+## Overview
+This model is a specialized Transformer designed to identify and suppress stochastic noise in superconducting quantum circuits. It processes raw pulse sequences or qubit telemetry to classify error types and provide a denoised representation of the underlying quantum state.
+
+
+
+## Model Architecture
+The architecture is based on a **Dense-Encoder Transformer** optimized for 1D signal sequences:
+- **Encoding Layers**: 6 Multi-head Self-Attention blocks.
+- **Dimensionality**: Reduced 512-hidden size for low-latency inference.
+- **Objective**: Minimization of the Mean Squared Error (MSE) between noisy input signals and pure state theoretical values:
+$$MSE = \frac{1}{n} \sum_{i=1}^{n} (Y_i - \hat{Y}_i)^2$$
+
+## Intended Use
+- **Real-time Error Mitigation**: Integrated into quantum controllers to correct bit-flip and phase-flip errors during gate execution.
+- **Telemetry Analysis**: Post-hoc processing of quantum experiment logs to improve readout fidelity.
+- **Calibration**: Assisting in the automated tuning of microwave pulse shapes.
+
+## Limitations
+- **Hardware Specificity**: Trained primarily on transmon qubit data; performance on ion traps or photonic systems may vary.
+- **High-Frequency Noise**: Limited by the sampling rate of the input signal; noise frequencies above 2GHz may result in aliasing artifacts.
+- **State Complexity**: Accuracy decreases as the depth of the quantum circuit (number of gates) increases significantly beyond the training horizon.